Supervised a team responsible for risk rating models and proactively resolved validation issues, ensuring model accuracy and compliance.Pioneered model monitoring automation by managing project timelines and delegating tasks, translating SAS codes to BigQuery and Python in GCP. Oversaw modeling methods, data processing, portfolio analysis, performance testing, and ensure robust model report generation along with code and results validation.Spearheaded the Machine Learning model development process, utilizing ensemble methods to determine and implement optimal models, enhancing overall model efficacy.

Validated response/approval rate models and card ratings using advanced techniques like XGBoost, Random Forest, MLP, and Gradient Boosting in Python.Engineered and implemented loss forecasting models utilizing Time Series, PCA, and LASSO regression in SAS and Python. Analyzed and adapted Credit Limit strategies during the COVID-19 pandemic, ensuring adaptive and effective risk management strategies.

Conducted comprehensive validations on credit risk models in wholesale and retail sectors, encompassing scorecard models and stress testing models across diverse lines of businesses.Created intricate models utilizing time series methods in R, ensuring their robustness and effectiveness. Conducted thorough validation data mining using SAS and R to enhance model performance.Delivered detailed model validation reports, categorized model risk tiers, and formulated enhancement strategies, establishing a quarterly review system to track and improve model performance.

Managed a team on model development of the Loss Forecasting Champion model for Auto Loan and Mortgage, employing MCMC, logistic regression, and linear regressions in SAS to ensure accurate forecasting and risk assessment.Orchestrated stakeholder relationships, guaranteeing alignment with senior management needs. Collaborated across departments to enhance methodologies, ensuring models met the organization's strategic objectives.

Independently conducted validations on credit risk models across diverse finance domains using SAS and Excel, ensuring accuracy and reliability.Offered valuable recommendations and actively maintained the enterprise-wide model inventory, managing macro factors in the database to ensure data integrity and reliability.

Provided strategic recommendations that enhanced margins in pricing activities and implemented automation in contract pricing processes using SAS, optimizing efficiency and accuracy.Developed statistical fixed effect models to precisely measure the impact of marketing promotion activities on retail sales, enabling data-driven decision-making.Supported fact-based decision-making in pricing activities, contributing analyses that led to strategic decisions and improved margins effectively.

Validated Operation Risk Loss Forecasting model using the MCMC semi-parametric algorithm, ensuring robustness and accuracy in risk assessment.Conducted comprehensive validations on Stress Testing Loss Forecasting models for diverse financial products, ensuring reliability and suitability across different scenarios.